Statistical Approach for Term Weighting in Very Short Documents for Text Categorization

Autor: Timonen, Mika, Kasari, Melissa

Publikováno v: Timonen, M & Kasari, M 2013, Statistical Approach for Term Weighting in Very Short Documents for Text Categorization . in A Fred, J L G Dietz, K Liu & J Filipe (eds), Knowledge Discover, Knowledge Engineering and Knowledge Management : 4th International Joint Conference, IC3K 2012 . Springer, Communications in Computer and Information Science, vol. 415, pp. 3-18, 4th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2012, Barcelona, Spain, 4/10/12 . https://doi.org/10.1007/978-3-642-54105-6_1

In this paper, we propose a novel approach for term weighting in very short documents that is used with a Support Vector Machine classifier. We focus on market research and social media documents. In both of these data sources, the average length of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=355e65625b88::1eba701de17825360184c5eae017e701
https://cris.vtt.fi/en/publications/4d9ef449-512b-4ea9-a684-781441a4482a

Modelling a Query Space Using Associations

Autor: Timonen, Mika, Silvonen, Paula, Kasari, Melissa

Publikováno v: Timonen, M, Silvonen, P & Kasari, M 2011, Modelling a Query Space Using Associations . in A Heimbürger, Y Kiyoki, T Tokuda, H Jaakkola & N Yoshida (eds), Information Modelling and Knowledge Bases XXII . IOS Press, Frontiers in Artificial Intelligence and Applications, vol. 225, pp. 77-96 . https://doi.org/10.3233/978-1-60750-690-4-77

We all use our associative memory constantly. Words and concepts form paths that we can follow to find new related concepts; for example, when we think about a car we may associate it with driving, roads or Japan, a country that produces cars. In thi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=355e65625b88::1c9d79be1aa176dbec2f6ad7fbde5766
https://cris.vtt.fi/en/publications/5ea277e4-042f-49e9-a07b-f44155a05a1e

Keyword Extraction from Short Documents Using Three Levels of Word Evaluation.

Autor: Timonen, Mika, Toivanen, Timo, Kasari, Melissa, Teng, Yue, Cheng, Chao, He, Liang

Publikováno v: Knowledge Discovery, Knowledge Engineering & Knowledge Management: 4th International Joint Conference, IC3K 2012, Barcelona, Spain, October 4-7, 2012, Revised Selected Papers; 2013, p130-146, 17p